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Anthony D. Phillips Department of Geography Ball State University

Flash Flooding Across the Southern Appalachians: An Abbreviated Climatology and Discussion M.S. Thesis Defense. Anthony D. Phillips Department of Geography Ball State University. Outline. Introduction Previous Research Research Focus Data and Methodology Results Statistical Analyses

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Anthony D. Phillips Department of Geography Ball State University

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  1. Flash Flooding Across the Southern Appalachians: An Abbreviated Climatology and DiscussionM.S. Thesis Defense Anthony D. Phillips Department of Geography Ball State University

  2. Outline • Introduction • Previous Research • Research Focus • Data and Methodology • Results • Statistical Analyses • Climatological Findings • Discussions with local WFOs • Brief Summary & Future Work • Questions A. Phillips — M.S. Thesis Defense

  3. What is Flash Flooding? • The NWS defines a flash flood as: • “Within six hours (often within one hour) of a causative event such as intense rain, dam break, or ice jam formation, one or more of the following occurs: • River or stream flows out of banks and is a threat to life or property. • Person or vehicle swept away by flowing water from runoff that inundates adjacent grounds. • A maintained county or state road closed by high water. • Six inches of fast-flowing water over a road or bridge. This includes low water crossings in a heavy rain event that is more than localized (i.e., radar and observer reports indicate flooding in nearby locations) and poses a threat to life or property. • Dam break or ice jam causes dangerous out-of-bank stream flows or inundates normally dry areas creating a hazard to life or property. • Any amount of water in contact with, flowing into, or causing damage to a residence or public building as a result of above ground runoff from adjacent areas. • …” A. Phillips — M.S. Thesis Defense

  4. The Flash Flood Threat • Residents of the southern mountains are at greater risk due to: • Steep, complex terrain • Rapid accumulation of precipitation • Competition with mountain streams for roads, bridges, housing, etc. • Mountaintop removal A. Phillips — M.S. Thesis Defense

  5. The Flash Flood Threat A. Phillips — M.S. Thesis Defense

  6. Previous Research • Several precipitation and flash flood climatologies have been developed over the past few decades. • Each defined flash flooding differently • Varying spatial and temporal scales • Three main climatologies focused on: • Maddox et al. (1979) • Gaffin and Hotz(2000) • Stonefield and Jackson (2009) A. Phillips — M.S. Thesis Defense

  7. Previous Research • Maddox et al. (1979) examined 151 flash floods that occurred between 1973 and 1977. • Reports from across the entire United States • Researched individual storm event reports for mentions of flash flooding. • Examined mesoscale and synoptic scale situations during flash floods • No specific criteria existed regarding what constituted a flash flood. • Reports often lacked information about timing, duration, and amount of precipitation. • Maddox firmly called for a national database to be developed. • Lead to the development of the database Storm Data. A. Phillips — M.S. Thesis Defense

  8. Previous Research • Maddox et al. (1979) discovered that 86 percent of flash floods in their study occurred during the warm season (April to September). • 25% occurred in the month of July. • They also found that a large segment of events occurred during the nighttime hours between 0600 and 1800 local time. Temporal frequency of events per month (from Maddox et al., 1979). A. Phillips — M.S. Thesis Defense

  9. Previous Research • Maddox et al. (1979) identified several characteristics common to almost all flash floods in their research: • Heavy rains were produced by convective storms. • Surface dew point temperatures were very high. • Large moisture contents were present through a deep tropospheric layer. • Convective storms and/or cells repeatedly formed and moved over the same area. • Vertical wind shear was weak to moderate through the cloud depth. • Storms often occurred during nighttime hours. A. Phillips — M.S. Thesis Defense

  10. Previous Research • Gaffin and Hotz (2000) examined flash floods over a 39-year period from 1960 to 1998. • Study was limited to the extent of the Morristown, TN WFO CWA. • Utilized records from Storm Data. • Synoptic patterns were also examined • Research ignored any type of urban flooding • Can be caused by even slight amounts of precipitation • Divided multi-county flash flood events into single events per county A. Phillips — M.S. Thesis Defense

  11. Previous Research • Gaffin and Hotz (2000) recognized a large percentage of flash flood reports occurred across counties with high population densities • Result of urban development along creeks and streams. • Counties with steep terrain had higher frequencies of flash flooding • Most destructive events occurred across these areas Number of flash flood reports by county across the WFO Morristown CWA between 1960 and 1998 (from Gaffin and Hotz, 2000). A. Phillips — M.S. Thesis Defense

  12. Previous Research • As with Maddox et al. (1979) , Gaffin and Hotz (2000) found that the month of July had the highest frequency of flash floods, followed by March and May, respectively. • Most events occurred during the afternoon and evening hours. Flash flood events per month across the Morristown, TN CWA (from Gaffin and Hotz, 2000). Flash flood events per time of day across the Morristown, TN CWA (from Gaffin and Hotz, 2000). A. Phillips — M.S. Thesis Defense

  13. Previous Research • Most recent flash flood climatology across the region is from Stonefield and Jackson (2009) • Very similar to research by Gaffin and Hotz (2000). • Events were compiled from the Storm Data database • They developed a severity classification scheme • Flood Severity Index (FSI) • Based on the impact (i.e., monetary damage) of individual flash flood events • Flash floods were ranked from FS1 (nuisance) to FS5 (catastrophic) A. Phillips — M.S. Thesis Defense

  14. Previous Research • 766 flash flood events were analyzed • County distributions • Annual, monthly, and hourly frequenices • Discovered that 75 percent of events occurred during the warm season • 25 percent occurred during June, followed by January • Large percentage of events occurred during afternoon and evening hours between 1200 and 2100 local time • 83 percent of flash floods were categorized as FS1 or FS2 events • Identified geographic regions prone to flash flooding Regions of synoptic-scale significant flash flood events (from Stonefield and Jackson, 2009). A. Phillips — M.S. Thesis Defense

  15. Research Focus • Created a climatology of flash flooding across the southern Appalachian Mountains using verifiable reports from the NCDC Storm Data database. • Analyzed the spatial and temporal extent of flash floods across the region. • Examined the influences of regional topography and social characteristics on the spatial distribution of flash floods. • Gathered information from local NWS WFOs about flash flood issues they are familiar with; specifically locations prone to flash flooding and meteorological conditions associated with heavy precipitation across the higher terrain. A. Phillips — M.S. Thesis Defense

  16. Data and Methodology • Defined the Southern Appalachians as: • Mountainous areas south of Mason-Dixon Line (~39.7° N) • Locations within the USGS Appalachian Highlands physiographic division; namely the Appalachian Plateau, Valley and Ridge, and Blue Ridge provinces • Data obtained from the National Climatic Data Center • Storm Data from 1950 to present (minus 6 months) • Focus on events after the Modernization and Associated Restructuring (MAR) of the NWS in the mid-1990’s • Storm reports and verification • Abbreviated climatology: January 1, 1996 to December 31, 2010 A. Phillips — M.S. Thesis Defense

  17. Data and Methodology A. Phillips — M.S. Thesis Defense

  18. Data and Methodology A. Phillips — M.S. Thesis Defense

  19. Data and Methodology • Number of events per county • Number of events per square kilometer • Number of events per county population • Mean number of events per year • Fatalities per county • Fatalities per county population • Injuries per county • Injuries per county population • Total damage incurred • Total property damage incurred • Total crop damage incurred • Number of events per county per year • Number of events per county per month • Number of FS1, FS2, FS3, FS4, and FS5 events per county • Fatality explanations • Hot spot analysis (Getis-OrdGi*) • Cluster and Outlier Analysis (Anselin Local Moran’s I) • Directional Distribution (Standard Deviational Ellipse) • Point density A. Phillips — M.S. Thesis Defense

  20. Results A. Phillips — M.S. Thesis Defense

  21. Results • Originally it was hypothesized that those counties with a higher frequency of flash floods also had higher mean percent slope values. • By comparing only the average slope to the number of flash floods per county, the findings suggest that this is not the case. A. Phillips — M.S. Thesis Defense

  22. Results • It was discovered that there is a positive relationship between the number of events per square kilometer and county population per square kilometer • Either a result of more people witnessing the flash flood ormore events actually occur over urbanized areas • From NWS discussions, most likely due to urban landscape A. Phillips — M.S. Thesis Defense

  23. Results A. Phillips — M.S. Thesis Defense

  24. Results • Poisson distribution was calculated to determine both the observed and predicted probability of a given number of flash floods occurring within a fixed area of 64.75 km2 (25 mi2). A. Phillips — M.S. Thesis Defense

  25. Results • Frequency of events per year • Noticeable variations, especially between drought (’99, ‘07) and non-drought years (‘03) A. Phillips — M.S. Thesis Defense

  26. Results • Number of events that occurred during each month • Frequency of events increases dramatically starting in May • Substantial decrease in October A. Phillips — M.S. Thesis Defense

  27. Results A. Phillips — M.S. Thesis Defense

  28. Results • Events per time of day divided into 1-hr increments • Number of events increases during afternoon/early night hours A. Phillips — M.S. Thesis Defense

  29. Results • Significant flash flood events per day and per hour • Same temporal clustering, but significant events occur later into the night • Events per day compared to events per hour • Clustering of events between April and September & 13:00 and 23:00 LST A. Phillips — M.S. Thesis Defense

  30. Results A. Phillips — M.S. Thesis Defense

  31. Results • Considerable number of fatalities due to children and young adults entering flood waters A. Phillips — M.S. Thesis Defense

  32. Results • Emails were sent to each WFO that serves the southern Appalachians asking for their thoughts on conditions favorable for flash flooding as well as any locations prone to events. • Eight of the thirteen WFOs responded with their insights • Their responses were compared to our derived climatology to determine if it was valid, some commonalities include: • Flash floods occur with greater frequency over urbanized areas and terrain highly influences the development and evolution of heavy precipitation storms, especially those that cause significant damage. • Nearly 75 percent of flash floods occur during the warm season from April to September. • June is typically the most active month for flash floods. • Most flash floods are nuisance or minor events, resulting in little to no damage. • Significant flash floods generally occur across rural counties. A. Phillips — M.S. Thesis Defense

  33. Summary • 4,938 unique flash flood reports from 1996 to 2010 • 71 fatalities and 64 injuries • As expected, greater number of events during warm season months and during afternoon/overnight hours • Correlation between number of events per km2 and population per km2 • Probability of a flash flood occurring within 64.75 km2 (25 mi2): 0.36 • Future work should include: • Expansion to include eastern U.S. • Further analysis of the synoptic and mesoscale environments associated with flash flooding A. Phillips — M.S. Thesis Defense

  34. Acknowledgements • Committee Chair: David A. Call, Ph.D. • Committee Members: Jill S. M. Coleman, Ph.D. Petra A. Zimmermann, Ph.D. Special thanks: • Stuart Hinson, NCDC, Asheville, NC • Various NWS Forecast Offices • BSU Department of Geography • Graduate Students A. Phillips — M.S. Thesis Defense

  35. Final Thoughts Any questions or comments? For more information: Anthony Phillips http://www.wx4sno.com wx4sno@vt.edu

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